Review changes

doc/source/getting_started/compatibility.rst

@@ -24,7 +24,7 @@ version.
 As new features are developed, every attempt is made to ensure backward
 compatibility from the client to the server. Backward compatibility is generally ensured for
 the four latest Ansys versions. For example, the ``ansys-dpf-core`` module 0.8.0 has been
-developed for Ansys 2023 R2 pre1 release, for 2023 R2 Ansys version. It is compatible with
+developed for the Ansys 2023 R2 version. It is compatible with
 2023 R2, 2023 R1, 2022 R2 and 2022 R1 Ansys versions.
 
 Starting with version ``0.10`` of ``ansys-dpf-core``, the packages ``ansys-dpf-gate``,

doc/source/operator_reference.rst

@@ -24,7 +24,7 @@ DPF operators allow you to manipulate and transform simulation data.
 
 
 For Ansys 2023 R2 and later, the DPF Server licensing logic for operators in DPF depends on the active
-server context.
+`server context<https://dpf.docs.pyansys.com/version/stable/api/ansys.dpf.core.server_context.html#ansys.dpf.core.server_context.ServerContext>`_.
 
 The available contexts are **Premium** and **Entry**.
 Licensed operators are marked as such in the documentation using the ``license`` property.

doc/source/user_guide/concepts/concepts.rst

@@ -13,7 +13,7 @@ Here are descriptions for key DPF terms:
 
 - **Data source**: One or more files containing analysis results.
 - **Field**: Main simulation data container.
-- **Field container**: For a transient, harmonic, modal, or multi-step
+- **Fields container**: For a transient, harmonic, modal, or multi-step
   static analysis, a set of fields, with one field for each time step
   or frequency.
 - **Location**: Type of topology associated with the data container. DPF

doc/source/user_guide/concepts/stepbystep.rst

@@ -23,7 +23,7 @@ Data can come from two sources:
 - **Manual input in DPF:** You can create fields of data in DPF.
 
 Once you specify data sources or manually create fields in DPF,
-you can create field containers (if applicable) and define scopings to
+you can create fields containers (if applicable) and define scopings to
 identify the subset of data that you want to evaluate.
 
 Specify the data source
@@ -103,27 +103,27 @@ This code shows how to define a mesh scoping:
    my_scoping.location = "Nodal" #optional
    my_scoping.ids = list(range(1,11))
 
-Define field containers
-~~~~~~~~~~~~~~~~~~~~~~~
-A **field container** holds a set of fields. It is used mainly for
+Define fields containers
+~~~~~~~~~~~~~~~~~~~~~~~~
+A **fields container** holds a set of fields. It is used mainly for
 transient, harmonic, modal, or multi-step analyses. This image
 explains its structure:
 
 .. image:: ../../images/drawings/field-con-overview.png
 
-A field container is a vector of fields. Fields are ordered with labels
-and IDs. Most commonly, a field container is scoped on the time label,
+A fields container is a vector of fields. Fields are ordered with labels
+and IDs. Most commonly, a fields container is scoped on the time label,
 and the IDs are the time or frequency sets:
 
 .. image:: ../../images/drawings/field-con.png
 
-You can define a field container in multiple ways:
+You can define a fields container in multiple ways:
 
 - Extract labeled data from a result file.
-- Create a field container from a CSV file.
-- Convert existing fields to a field container.
+- Create a fields container from a CSV file.
+- Convert existing fields to a fields container.
 
-This code shows how to define a field container from scratch:
+This code shows how to define a fields container from scratch:
 
 .. code-block:: python
 
@@ -137,9 +137,9 @@ This code shows how to define a field container from scratch:
        mscop = {"time":i+1,"complex":1}
        fc.add_field(mscop,dpf.Field(nentities=i+10))
 
-Some operators can operate directly on field containers instead of fields.
-Field containers are identified by ``fc`` suffixes in their names.
-Operators and field containers are explained in more detail
+Some operators can operate directly on fields containers instead of fields.
+Fields containers are identified by ``fc`` suffixes in their names.
+Operators and fields containers are explained in more detail
 in :ref:`transform_the_data`.
 
 .. _transform_the_data:
@@ -157,9 +157,9 @@ You use operators to import, export, transform, and analyze data.
 An operator is analogous to an integrated circuit in electronics. It
 has a set of input and output pins. Pins pass data to and from operators.
 
-An operator takes input from a field, field container, or scoping using
+An operator takes input from a field, fields container, or scoping using
 an input pin. Based on what it is designed to do, the operator computes
-an output that it passes to a field or field container using an output pin.
+an output that it passes to a field or fields container using an output pin.
 
 .. image:: ../../images/drawings/circuit.png
 

doc/source/user_guide/fields_container.rst

@@ -1,22 +1,22 @@
 .. _ref_user_guide_fields_container:
 
-===========================
-Field containers and fields
-===========================
-While DPF uses operators to load and operate on data, it uses field containers
+============================
+Fields containers and fields
+============================
+While DPF uses operators to load and operate on data, it uses fields containers
 and fields to store and return data. Operators are like verbs, acting on the data, 
-while field containers and fields are like nouns, objects that hold data.  
+while fields containers and fields are like nouns, objects that hold data.  
 
-Access a field container or field
+Access a fields container or field
 -----------------------------------
 The outputs from operators can be either a 
 :class:`ansys.dpf.core.fields_container.FieldsContainer` or 
 :class:`ansys.dpf.core.field.Field` class.
 
-A field container is the DPF equivalent of a list of fields. It holds a
+A fields container is the DPF equivalent of a list of fields. It holds a
 vector of fields.
 
-This example uses the ``elastic_strain`` operator to access a field container:
+This example uses the ``elastic_strain`` operator to access a fields container:
 
 .. code-block::
 
@@ -58,11 +58,11 @@ This example uses the ``elastic_strain`` operator to access a field container:
       - field 19 {time:  20} with ElementalNodal location, 6 components and 40 entities.
 
 
-Access fields within a field container
---------------------------------------
+Access fields within a fields container
+---------------------------------------
 Many methods are available for accessing a field in a field
 container. The preceding results contain a transient
-result, which means that the field container has one field
+result, which means that the fields container has one field
 by time set. 
 
 Access the field:
@@ -189,7 +189,7 @@ Here is a more real-world example:
  
 
 The following example references the available time frequency support to determine which
-time complex IDs are available in the field container:
+time complex IDs are available in the fields container:
 
 .. code-block::
 

doc/source/user_guide/operators.rst

@@ -334,8 +334,8 @@ Operators for transforming data
 *******************************
 
 A field is the main data container in DPF. Most of the operators that transform
-data take a field or a field container as input and return a transformed 
-field or field container as output. You can perform analytic, averaging, 
+data take a field or a fields container as input and return a transformed 
+field or fields container as output. You can perform analytic, averaging, 
 or filtering operations on simulation data.
 
 For example, after creation of a field, you can use scaling and filtering 

doc/source/user_guide/server_types.rst

@@ -9,7 +9,7 @@ Terminology
 
 DPF is based on a **client-server** architecture. 
 
-A DPF Server is a set of files that enable DPF capabilities.
+A DPF Server is a set of files that enables DPF capabilities.
 
 PyDPF-Core is a Python client API communicating with a DPF Server, either
 directly **in the same process** or through the network using **gRPC**.